Fog-based Remote in-Home Health Monitoring Framework

As a result of what happened to the world during the past and current year of the spread of the Covid-19 epidemic, it was necessary to have a reliable health care system for remote observation, especially in care homes for the elderly. There are many research works have been done in this field, but still have limitations in terms of latency, security, response delay, and long execution times. To remove these limitations, this paper introduces a Smart Healthcare Framework called Remote in-Home Health Monitoring (RHHM), which provides architecture and functionalities in order to facilitate the control of patients' conditions when they are at home. The framework exploits the benefits of fog layers with high-level services such as local storage, local real-time data processing, and embedded data mining for taking responsibility for handling some burdens of the sensor network and the cloud and to become a decision maker. In addition to, it incorporates camera with body sensors in diagnosis for more reliability and efficiency with privacy preserving. The performance of the proposed framework was evaluated using the popular iFogSim toolkit. The results show the proposed system's ability to reduce latency, energy consumption, network communications, and overall response time. The efforts of this work will help support the overall goal to establish a high performance, secured and reliable smart Healthcare system.